Quillworts from the Amazon: A multidisciplinary populational study on Isoetes serracarajensis and Isoetes cangae
Bibliographic record
Abstract
Isoetes are ancient quillworts members of the only genus of the order Isoetales. The genus is slow evolving but is resilient, and widespread worldwide. Two recently described species occur in the Eastern Brazilian Amazon, Isoetes serracarajensis and Isoetes cangae. They are found in the ironstone grasslands known as Canga. While I. serracarajensis is present mostly in seasonal water bodies, I. cangae is known to occur in a single permanent lake at the South mountain range. In this work, we undertake an extensive morphological, physiological and genetic characterization of both species to establish species boundaries and better understand the morphological and genetic features of these two species. Our results indicate that the morphological differentiation of the species is subtle and requires a quantitative assessment of morphological elements of the megaspore for diagnosis. We did not detect differences in microspore output, but morphological peculiarities may establish a reproductive barrier. Additionally, genetic analysis using DNA barcodes and whole chloroplast genomes indicate that although the plants are genetically very similar both approaches provide diagnostic characters. There was no indication of population structuring I. serracarajensis. These results set the basis for a deeper understanding of the evolution of the Isoetes genus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".